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Jurnal Riset Informatika

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Published by KresnaMedia Publisher

ISSN : 26561743 EISSN : 26561735 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik Informatika.

Arjuna Subject : -

Articles 417 Documents

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SALES LEVEL ANALYSIS USING THE ASSOCIATION METHOD WITH THE APRIORI ALGORITHM Samuel Samuel; Asrul Sani; Agus Budiyantara; Merliani Ivone S; Frieyadie Frieyadie
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

The company does not yet know the pattern of consumer purchases because, so far, the sales transaction data has not been used correctly and does not have a unique method to determine consumer buying patterns. The problems on the company, this research was done to reprocess sales transaction data for 2018-2019 using data mining techniques with association methods and apriori algorithms. RapidMiner is a supporting application to find association rules derived from transaction data. Processed transaction data using the Knowledge Discovery in Database approach. Thus, the company can determine consumer habits in buying goods from sales transaction data for 2018-2019. The results of this study are that in 2018, nine association rules were obtained, of which the best were CT G-246 ⇒ CT G-250 and CT G-250 ⇒ CT G-246. In 2019, nineteen association rules were received, of which the best were PN 0441, SK 0175 ⇒ SK 0530, and SK 0175, SK 0283, ⇒ SK 0530. From the best association rules, the goods in the Coat (imported), Pants, and Skirt categories are often bought together.

A REQUIREMENT ENGINEERING IN REPORTING AND COUNSELING-BASED ASSISTANCE APPLICATION FOR VICTIMS OF VIOLENCE AGAINST WOMEN Dwi Hosanna Bangkalang; Nina Setiyawati; Radius Tanone; Hanna P. Chernovita; Yuliana T. B. Tacoh
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

Requirements engineering is the initial phase of the software development life cycle it is a critical aspect of application development since it has a significant impact on the results of the product being created. This article focuses on the engineering requirements of the web-based application development process for reporting and assisting victims of violence against women using the Loucopoulos and Kanakostas Iterative Requirements Engineering Process Model. The application was created to contribute to the solution of the problem of violence against women in Indonesia, where violence against women is an iceberg phenomenon because not all incidents are reported. Furthermore, victims of violence against women require support in receiving emotional support in the form of counseling, which can be done online via chat or video calls. The results of these requirements engineering are alternative solutions, application feature design, database design, system modeling using UML, and application architecture design. The validation of requirements engineering was carried out using a low fidelity prototype

Identifying Skin Cancer Disease Types With You Only Look Once (YOLO) Algorithm Ninuk Wiliani; Anita Putri Valeria Dhiu Lusi; Nur Hikmah
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

The skin is the outermost vital organ and is susceptible to various diseases, including skin cancer. The number of cases of skin cancer around the world continues to increase every year, including in Indonesia. Proper handling is critical to cure skin cancer, and one of the solutions that can be used is the Deep Learning method. This study aims to apply the Deep Learning method, specifically an object detection algorithm called You Only Look Once (YOLO), for early skin cancer detection. The YOLOv5s algorithm is the model for this study because it is accurate and can detect objects in real-time. The research method involved collecting data on skin cancer cases and training the YOLOv5s model. After training, model testing is used to evaluate the ability to detect skin cancer. The test results show that the YOLOv5s model has an accuracy of 89.1% in detecting skin cancer types. This research has important implications in the health sector, especially in early skin cancer detection.

SELECTION OF THE BEST PREWEDDING PHOTO LOCATION USING THE AHP METHOD Muhammad Noval Alfarizi; Mariah Nur Azizah; Wikara Dwi Saputra; Siti Ernawati
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

The location of the photo prewedding is a place that can describe the happiness of the bride and groom. In these conditions sometimes the general public especially prospective bride and groom and the photographer have difficulty in choosing the location of the photo prewedding best. Then the resulting decision-makers will get the location of the photo prewedding which is not in accordance with what is expected. In this study utilizes the Method of Analytical Hierarchy Process (AHP) to help the bride and groom and the photographer in choosing the location of the photo prewedding best, especially in the area of Jakarta. This study using six criteria such as distance, number of spots, transportation, time, cost, location, and theme. From the Results of the analysis and processing of the data obtained that the Ancol with superior value 0,224047721 (22%) berbandingan to cafe batavia with a value of 0,195494507 (20%), sunda kelapa harbor to the value 0,187335550 (19%), taman wisata mangrove angke kapuk with a value of 0,171584976 (17%), old city, with the value of 0,162696386 (16%), and glodok, with a value of 0,058840858 (6%).

House Price Prediction Using Data Mining with Linear Regression and Neural Network Algorithms Palupi, Endang
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

The need for housing in big cities is very high because most offices and economic centers are in big cities. Limited land and high demand cause house prices to rise. Many developers build housing on the outskirts of big cities with access to trains and toll roads to make transportation easier. Property developers compete by providing the best prices, various choices of house specifications, ease of the mortgage process, and attractive promotions such as no down payment. A house is a long-term investment whose price increases yearly, so proper analysis is needed to buy a place to live in. Several factors influence the price of a house, including location, land area, building area, building type, and so on. This research aims to create a house price prediction model using the Linear Regression Algorithm and Neural Network so that the results can be useful for property agents in predicting house sales or from the buyer's side in predicting house prices. The results of this research use the Linear Regression Algorithm RMSE 0.775, while the Neural Network Algorithm uses RMSE 0.645. From this research, modeling using the Linear Regression Algorithm has better results. Still, the Linear Regression Algorithm and Neural Network Algorithm have RMSE results that are close to accurate and have small errors.

AN EDUCATIONAL GAME APPLICATION TO ASSIST THE COMMUNITY IN REMEMBERING ROAD DIRECTIONS AND PLACES IN PALEMBANG Nadya Angelia; Miftahul Jannah; Albert Amadeus Valentino; Michelle Liu; Ali Ibrahim
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Visuospatial processing is one of the important aspects of everyday life, whether it is to travel or to recognize the location of objects around. Visuospatial processing can be improved in various way, one of which is by using repetition. WorldVenture app was created to help its users improve their visuospatial capability by remembering landmarks in the city where they live. WorldVenture was created using flutter framework with five steps, namely literature study, data and information collection, application designing, testing, and evaluation. This app will have three main features: Flashcard, Quiz, and Notes. WorldVenture testing result, using questionnaires, showed 64,5% people out of 30 respondents rated WorldVenture excellent for improving visuospatial capabilities and as many as 35.5% of respondents rated it good.

Phrase Detection's Impact on Sentiment Analysis of Public Opinion and online Media Toward Political Figures Nurodin, Muhammad Irsa; Yan Puspitarani
Jurnal Riset Informatika Vol. 6 No. 2 (2024): March 2024
Publisher : Kresnamedia Publisher

Public opinion of political figures and policy significantly impacts general elections. Sentiment analysis, as a method to comprehend opinion and emotion in texts, requires the step of text preprocessing to improve data quality. However, textual data often encounters irrelevant words and ambiguous language. These conditions can impact the accuracy of sentiment analysis. Given the significance of precisely interpreting public opinion toward political figures, these issues may result in biased or inaccurate sentiment analysis outcomes. Irregular punctuation or unclear language can disturb the text's intended context, compromising sentiment analysis quality. Additionally, irrelevant words can obscure the focus of the analysis, causing fundamental changes in the original text's meaning. This research focuses on the impact of a specific preprocessing technique, namely Phrase Detection with N-Gram, on sentiment analysis of political figures. By applying this method, the study aims to detail the effects of using Bigram, Trigram, and Unigram on the quality of sentiment analysis, particularly in the context of political figures on Twitter and online media articles. This research indicates that using Bigram in Phrase Detection provides more significant results than Trigram and Unigram for most political figures at Twitter, with the highest accuracy score of 88,23%. Sentiment analysis of articles in online media also indicates various results depending on the type of N-Gram. The results indicate that using N-gram phrase detection can influence the accuracy of sentiment analysis, and the resulting accuracy values are pretty high.

Approaches to Customer Types Classification Method in the Supermarket Nanang Ruhyana; Mardiana, Tati
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

The development of the retail industry in the economy is very rapid so it provides good economic growth, one of the retailers is supermarkets, in supermarkets consumers can buy goods directly, so consumers must be served well. The problem is how supermarkets can continue to increase their sales results, because there is a lot of competition from supermarket competitors, so the marketing team when creating events or promotions must be right on target so that loyalty for member or non-member customers can be measured, which will be used as the right marketing strategy and can increase customer satisfaction when the customer is satisfied with the services, products and promotional activities at the supermarket, the customer will continue to make purchases and will increase the results of achieving good sales. Based on this problem, how will this research apply the classification method, so that when we can make predictions from supermarket sales data for member and non-member customers, there will be a lot of insight for the marketing team, so that marketing activities are right on target for member or non-member customers. This research uses machine learning methods for data classification, using the Support Vector Machine (SVM) and Naïve Bayes algorithms. The results of this research are from the Support Vector Machine (SVM) algorithm. Accuracy is 0.493 while using the Naïve Bayes algorithm is 0.535. From the results of this research, the use of the Naïve Bayes algorithm is better than SVM so that it can approach the prediction of member and non-member customer classification in supermarket data in this research.

Simulation of Small-Scale Solar Power Generation System in The Central Java Region: A Case Study of the Cilacap Area Lee, Vincentius Rayza; Saputri, Fahmy Rinanda
Jurnal Riset Informatika Vol. 6 No. 2 (2024): March 2024
Publisher : Kresnamedia Publisher

The limitations of conventional non-renewable energy resources raise concerns about sustainability and energy supply security in the future. One of the worrying factors is the carbon dioxide emissions that can affect living organisms' health. Renewable energy sources, such as solar, wind, and hydropower, emerge as solutions capable of minimizing environmental impacts and reducing dependence on limited resources. Therefore, this research will simulate and design a small-scale renewable energy power generation system, particularly solar energy, in the Cilacap region, Central Java. The main components involved in this research include PV arrays, IGBT diodes, and universal bridges, supported by supporting elements such as displays, scopes, resistors, capacitors, inductors, and bus selectors. The technical data used as input are specific to the area. The simulation results show that the direct power generated by one modelled PV array is 221.7 W per hour. This research contributes to optimising small-scale solar power generation systems in the designated area, considering relevant components and parameters to enhance efficiency and sustainability.

DEVELOPMENT OF MANUFACTURING INVENTORY MANAGEMENT SYSTEM USING MATERIAL REQUIREMENT PLANNING METHOD Ami Rahmawati; Rizal Amegia Saputra; Ita Yulianti
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Inventory has an important role in business activities. This is because inventory has an effect on changes in the production market and anticipates price changes in the demand for many goods. PT. Barkah Jaya Mandiri is a company engaged in manufacturing where the management of inventory at the company is still done conventionally. This causes various problems such as the occurrence of discrepancies in the stock of goods, discrepancies in data and final reports as well as obstacles in the production process in the event of a shortage or excess of raw materials. (Material Requirement Planning) in order to overcome the problems that occur in the company. The combination of the SDLC model and data collection techniques including observation, interviews and literature study were also carried out in this study in order to achieve the system that will be built to suit the targeted needs. With this system, the management of inventory data at this company can be done easily and accurately and save time compared to the previous system, so that the procurement of manufacturing raw materials is optimal and employee performance is better.

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Tati Mardiana

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Journal Mail Official
jurnal.jri@kresnamediapublisher.com

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Location
Kota banjar,

Jawa barat

INDONESIA